Dongya Wu
Impact in
- Signal Processing top 5%
- Time Series Analysis and Forecasting
- Music and Audio Processing
- Artificial Intelligence top 5%
- Anomaly Detection Techniques and Applications
Papers in
-
- Functional Brain Connectivity Studies 7
- Co-authors
- Huanzhang Lu (6 shared papers)Bendong Zhao (5 shared papers)Junliang Liu (2 shared papers)Shangfeng Chen (1 shared paper)Tianzi Jiang (4 shared papers)Guiqian Tang (1 shared paper)Yonghong Wang (1 shared paper)Yuepeng Pan (1 shared paper)
In The Last Decade
Dongya Wu
29 papers receiving 847 citations
Hit Papers
Peers
Comparison fields: 5 of 127
- Signal Processing 208
- Artificial Intelligence 280
- Cognitive Neuroscience 96
- Computer Vision and Pattern Recognition 88
- Atmospheric Science 74
Countries citing papers authored by Dongya Wu
This map shows the geographic impact of Dongya Wu's research. It shows the number of citations coming from papers published by authors working in each country. You can also color the map by specialization and compare the number of citations received by Dongya Wu with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Dongya Wu more than expected).
Fields of papers citing papers by Dongya Wu
This network shows the impact of papers produced by Dongya Wu. Nodes represent research fields, and links connect fields that are likely to share authors. Colored nodes show fields that tend to cite the papers produced by Dongya Wu. The network helps show where Dongya Wu may publish in the future.
Co-authors
The 25 scholars most cited alongside Dongya Wu, linked wherever they have co-authored with each other. Click a name or a connecting line to browse the papers they share.
All Works
Showing the 20 most-cited of 30 papers — load more, or switch the sort, to bring in the rest.
| # | Work | ||
|---|---|---|---|
| 1 | Convolutional neural networks for time series classification Hit paper breakdown → | 2017 | 593 |
| 2 | 2013 | 61 | |
| 3 | 2019 | 30 | |
| 4 | 2019 | 29 | |
| 5 | 2018 | 29 | |
| 6 | 2010 | 20 | |
| 7 | 2020 | 18 | |
| 8 | 2022 | 14 | |
| 9 | 2019 | 12 | |
| 10 | 2021 | 11 | |
| 11 | 2019 | 9 | |
| 12 | 2019 | 6 | |
| 13 | 2021 | 5 | |
| 14 | 2019 | 4 | |
| 15 | 2023 | 3 | |
| 16 | 2020 | 3 | |
| 17 | 2023 | 3 | |
| 18 | 2019 | 3 | |
| 19 | 2023 | 3 | |
| 20 | 2019 | 3 |
About Dongya Wu
Dongya Wu is a scholar working on Cognitive Neuroscience, Signal Processing, Computational Mechanics, Experimental and Cognitive Psychology and Electrical and Electronic Engineering, having authored 30 papers that have together received 874 indexed citations. Recurring topics across this work include Functional Brain Connectivity Studies (7 papers), Sparse and Compressive Sensing Techniques (6 papers), Statistical Methods and Inference (4 papers), Infrared Target Detection Methodologies (4 papers), Advanced Neuroimaging Techniques and Applications (3 papers), Emotion and Mood Recognition (3 papers), Advanced MRI Techniques and Applications (3 papers) and Advanced Measurement and Detection Methods (3 papers). The work is most often cited by research in Signal Processing (208 citations), Artificial Intelligence (280 citations), Cognitive Neuroscience (96 citations), Computer Vision and Pattern Recognition (88 citations) and Atmospheric Science (74 citations). Dongya Wu has collaborated with scholars based in China, Australia and Taiwan. Frequent co-authors include Huanzhang Lu, Bendong Zhao, Junliang Liu, Shangfeng Chen, Tianzi Jiang, Guiqian Tang, Yonghong Wang, Yuepeng Pan, Xin Li and Jun Feng. Their work appears in journals such as Brain Imaging and Behavior, Electric Power Systems Research, Computational Statistics & Data Analysis, Electronics and BMC Bioinformatics.
Rankless uses publication and citation data sourced from OpenAlex, an open and comprehensive bibliographic database. While OpenAlex provides broad and valuable coverage of the global research landscape, it—like all bibliographic datasets—has inherent limitations. These include incomplete records, variations in author disambiguation, differences in journal indexing, and delays in data updates. As a result, some metrics and network relationships displayed in Rankless may not fully capture the entirety of a scholar's output or impact.